Skripsi

ANALISIS PERBANDINGAN DETECTION TRAFFIC ANOMALY SERANGAN DDoS IPv4 DENGAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (SVM). 

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Penilaian

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Anomaly traffic is a condition that results in an abnormality in network traffic. Anomaly detections is a monitoring to monitor the movement that occurs in the network system. DDoS attack or Distributed Denial of Service is a cyber attack by continuously sending fake traffic to a system or server. As a result, the server cannot manage all traffic, causing it to go down. In this research, traffic anomaly detection will be carried out using the naïve Bayes method and support vector machine to see a comparison of the two methods used in the detection of IPv4 ddos attacks. The results show that using the Naïve Bayes algorithm method produces an accuracy value of 99.68%, 99.68% precision, 99.68% recall, and 99.68% F1 score which is proven to be better than the Support Vector Machine method which produces an accuracy value of 85 .79%, 83.79% precision, 88.83% recall, and 86.24% F1 score in detecting traffic anomalies against DDoS attack data packets and normal data.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307001396	T92422	T924222023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T924222023

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

viii, 74 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.707

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Data dalam sistem-sistem komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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